Transaction
ID: db8eadef6d...ad15
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
6.38 ERG
Tokens:
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Outputs (19)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3.75 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.4 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Transaction Details
Confirmations: 715,361
Total coins transferred: 6.39 ERG
Fees: 0.005 ERG
Fees per byte: 0.000000211 ERG
Raw Transaction Data
{
"id": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"inclusionHeight": 1057317,
"timestamp": 1690611828119,
"index": 17,
"globalIndex": 5588999,
"numConfirmations": 715361,
"inputs": [
{
"boxId": "68c636edd5eb22657a13325c620d2800f1f2d69435ddc174f9fa29b2337f36c7",
"value": 11000000,
"index": 0,
"spendingProof": "861663272903aa8aaeead4921fbbc95bc669ca4c512c30ff3aec5e34890b30ec54c95e31b26a0260f7069c2179333939c66c0e7b1f252afe",
"outputBlockId": "930a209a502582063cc07e2170aec895b6a424083ba0f98cb329685a26e5afd9",
"outputTransactionId": "acdc48b2ceca7848e36568ee610f3c3da9e531bdce3ba61c482b687b35c2f1fe",
"outputIndex": 0,
"outputGlobalIndex": 31352765,
"outputCreatedAt": 1057297,
"outputSettledAt": 1057300,
"ergoTree": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(4970f9,ce1e2c,...)))}",
"address": "9h29eioRvrL86Sabpecor9ag6rfXEGQt7U3K9q3Di1fdA4jVEsp",
"assets": [
{
"tokenId": "147b4234ded25a11d186cee547cf2440856aa4a64b1c47e4fde32353dc57b9e7",
"index": 0,
"amount": 1,
"name": "Mage Champions #1008",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "090eda4bd30c346093ed13d609b1dd84047886405f7081ad39054163f2ccd479",
"index": 1,
"amount": 1,
"name": "Mage Champions #1210",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "067833a1b946acbc13ea379af1a94f81b6750c5a717c880e7abd76c093d5da67",
"index": 2,
"amount": 1,
"name": "Mage Champions #2",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "8f458fe862d39335737f8d0d334c718735538584d4b7f0cb6acfef1a3c0bde34",
"index": 3,
"amount": 1,
"name": "Mage Champions #498",
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"type": "EIP-004"
},
{
"tokenId": "959ad19b2c6c9e1f8aeeba81a6d4b2ad030f88f757e13e8ffbed8bde60db1dba",
"index": 4,
"amount": 1,
"name": "Mage Champions #507",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "a011acc4d0a6f622e0f34fd78f8460d468397526efe5a0333513a3ee4abac2be",
"index": 5,
"amount": 1,
"name": "Mage Champions #513",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "44f909f37d1a75f27727ee8e6249f2e5a28dde67f7f0840d1a0b5d24e6a1c21b",
"index": 6,
"amount": 1,
"name": "Mage Champions #57",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "44faacf022822e163f159e81c11465e2e0f124618804c9bd763f21d96c4e97c1",
"index": 7,
"amount": 1,
"name": "Mage Champions #58",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "489a692796df6dd36cedf230942c1c325ddd8139048e0ec70a58d1f68d80687d",
"index": 8,
"amount": 1,
"name": "Mage Champions #60",
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"type": "EIP-004"
},
{
"tokenId": "145120c415b16205c37c2d75f29743133ebaf4ffb5470d99c45c7c23490f76f2",
"index": 9,
"amount": 1,
"name": "Mage Champions #611",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "2a03c98de16ea6ade7f5ac4ed1ab4179d154bffd6c86514ca63de56eb333ef68",
"index": 10,
"amount": 1,
"name": "Mage Champions #623",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "5e9bccda667dd05666d4a01f341d995540aa4cea6ebf3a33aff9658491b6db4f",
"index": 11,
"amount": 1,
"name": "Mage Champions #866",
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"type": "EIP-004"
},
{
"tokenId": "759692e2bb40310ced36b2c337cba7a0395ba7c51cfd2251c9ad026e0dff3b0e",
"index": 12,
"amount": 1,
"name": "Mage Champions #880",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "8e42f722117b8a78b5707a4e395aa68d18d86327fd09d2f8dcf21e138da93726",
"index": 13,
"amount": 1,
"name": "Mage Champions #903",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "73142be13954618a0704f3f475d0cc12a8470074068e0e82c2be00d14054c03b",
"index": 14,
"amount": 1,
"name": "Mage Champions #94",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "b88d217951d720cb574560c671cdcf814758d233a84060cdb85fa0f1513c6d35",
"index": 15,
"amount": 1,
"name": "Mage Champions #940",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "ca27beb16bb6076def305797aa4d505c01be052b409c5a8b902309bd1763e554",
"value": 6380099400,
"index": 1,
"spendingProof": "29f5e3292b2bc2953d2b151b72e02600c8f829b4828bc29c27764132e9793698479e7537f37333212f2ae20f51a8851b09e3e5bd4889736f",
"outputBlockId": "3d5f9818e162e28ffb0b0425fe69a38fde1ffc5b284a398684ae936341e55968",
"outputTransactionId": "d2d08314154ae7ffebbfcc7ab647d31db1ca241267aead17564b6336774c8c47",
"outputIndex": 0,
"outputGlobalIndex": 31351557,
"outputCreatedAt": 1057255,
"outputSettledAt": 1057257,
"ergoTree": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(4970f9,ce1e2c,...)))}",
"address": "9h29eioRvrL86Sabpecor9ag6rfXEGQt7U3K9q3Di1fdA4jVEsp",
"assets": [
{
"tokenId": "902d3495f7d86039cc3daf803b5b2c3858a0435774f8a6098b97729751ab4030",
"index": 0,
"amount": 1,
"name": "Cybercitizen #1470",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "9634e67093b893a933b10c3ffd025c8891db1167f8e108ac038178c2df48862d",
"index": 1,
"amount": 1,
"name": "Cybercitizen #1528",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "9afea298b004e7798e6cb101ac4c7ac1ad6b9f1bd997df49c6fe24c03edc3d61",
"index": 2,
"amount": 1,
"name": "Cybercitizen #1583",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "423ec6e3f7235f1cc4f3a6e90cd4f50ce34b20b3cdd3c557564d303d21d92c1e",
"index": 3,
"amount": 1,
"name": "Cybercitizen #599",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "4703093818fdc46e27e96ef83680dbf254fc2960600cf900c15eb2aa266ce4f6",
"index": 4,
"amount": 1,
"name": "Cybercitizen #657",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "4f3cc10288c47e2332f113650d21a2f358a52d5ab7fb2f4df5127f3bacbe86cd",
"index": 5,
"amount": 1,
"name": "Cybercitizen #756",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1c80c0570397f6082feb429dfc73c3510bdfd6a1cdc61b67ace98742fb429233",
"index": 6,
"amount": 1,
"name": "Cybercitizen #211",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "538edf0244cb0f1f20903bf46e3e839ba144defa8803a4944957cca8ab1b8916",
"index": 7,
"amount": 1,
"name": "Cybercitizen #808",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "b2e6190a84ccab42b2d1eaecb8edbccd5eaa57290edb853b4b633ba88877b7f2",
"index": 8,
"amount": 1,
"name": "Cybercitizen #1843",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "91289d5cefb9d78e3ea248d4e9c5b0e3c3de54f64bfae85c0070580961995262",
"index": 9,
"amount": 10000,
"name": "PEPERG",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "573d9010b852894b9f99bc072933e6cfa115b490f857451e385dbc2e8448cf7c",
"value": 4219364,
"index": 0,
"outputBlockId": "b3cfb684232fe21e89a8132c966b08c6772b72369822c397d25a7bc8e98c9bda",
"outputTransactionId": "aa58e9d389d3044fda4201159d5d62752e0820f8d0b8506cec28ac4fd0ea826e",
"outputIndex": 0,
"ergoTree": "0008cd03b04048a9708f0a2b109d75513a2483e3b9ede622efb3cc03bdddf93bccd93ac5",
"address": "9hoRnjysKfkwZSCgSFNzSXMohwYn8DqruuYxD6vT7Ubw55qnwiZ",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "0e240008cd03d4e3f9c9956945986a2bc2621a2fc02b9f7492fe57c87be07a33a0d7ccef5bc8",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd03d4e3f9c9956945986a2bc2621a2fc02b9f7492fe57c87be07a33a0d7ccef5bc8"
},
"R6": {
"serializedValue": "0580dac409",
"sigmaType": "SLong",
"renderedValue": "10000000"
},
"R8": {
"serializedValue": "058084af5f",
"sigmaType": "SLong",
"renderedValue": "100000000"
},
"R7": {
"serializedValue": "110280dddb0180fca402",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1800000,2400000]"
},
"R4": {
"serializedValue": "0428",
"sigmaType": "SInt",
"renderedValue": "20"
}
}
}
],
"outputs": [
{
"boxId": "df181bdb24f05f3541e07efee66084a914a02ae4d712af810839ba96b4d95f52",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 0,
"globalIndex": 31354004,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "067833a1b946acbc13ea379af1a94f81b6750c5a717c880e7abd76c093d5da67",
"index": 0,
"amount": 1,
"name": "Mage Champions #2",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "6a171af47ab2db5b7dda9644734a162573c045fe0a70e4f2285bfd97de79b4da",
"mainChain": true
},
{
"boxId": "9024f6c4ba1afe40dd903824c3883882ee3e9bc91d98c05f94235f33bb147a8f",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 1,
"globalIndex": 31354005,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "73142be13954618a0704f3f475d0cc12a8470074068e0e82c2be00d14054c03b",
"index": 0,
"amount": 1,
"name": "Mage Champions #94",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "7bcb8c97591271a35c5c3bdfb26a92c9d919fcfa9b19bd21ce62b0dabf4eb153",
"mainChain": true
},
{
"boxId": "6f51d23a8848aa1fd911a358982936cbec5f65112bba367b23405e244f3f84d2",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 2,
"globalIndex": 31354006,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "44faacf022822e163f159e81c11465e2e0f124618804c9bd763f21d96c4e97c1",
"index": 0,
"amount": 1,
"name": "Mage Champions #58",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "553ffbd8a9e93ae14ca0b1c25a9f9e6f4f7ed58e93ef3157df265cac0f9ec313",
"mainChain": true
},
{
"boxId": "a262767c2761666126bcc9ea910b2fc4d0713a2a5f8bdad87af9e55cdd371047",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 3,
"globalIndex": 31354007,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "8f458fe862d39335737f8d0d334c718735538584d4b7f0cb6acfef1a3c0bde34",
"index": 0,
"amount": 1,
"name": "Mage Champions #498",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "0cb9811c9a6fa3a54c390722af1a5ffefa808728352e9aa1d0f55a40f7018e4c",
"mainChain": true
},
{
"boxId": "49af522e6d7b3e5406567210b81c0d9b578f01943bd626b4f6137eaa36bb8ba7",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 4,
"globalIndex": 31354008,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "145120c415b16205c37c2d75f29743133ebaf4ffb5470d99c45c7c23490f76f2",
"index": 0,
"amount": 1,
"name": "Mage Champions #611",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "a9c183981ed86447895a3c9f9a3e7de4d1995ac35b0c3bd6ee138faa149f4fda",
"mainChain": true
},
{
"boxId": "38859a218c105310a82371054866c3084b54141785c68cdce00bc856b233ba97",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 5,
"globalIndex": 31354009,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "489a692796df6dd36cedf230942c1c325ddd8139048e0ec70a58d1f68d80687d",
"index": 0,
"amount": 1,
"name": "Mage Champions #60",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "2113710db07679e777b95f8fd42cb4d3810434635a6199b8b4f6f95c197e5747",
"mainChain": true
},
{
"boxId": "9d1a0fcf043461a6d3456c25de54e6bc0d8307d863f14f1eaaa70c07d970482c",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 6,
"globalIndex": 31354010,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "44f909f37d1a75f27727ee8e6249f2e5a28dde67f7f0840d1a0b5d24e6a1c21b",
"index": 0,
"amount": 1,
"name": "Mage Champions #57",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "08a51189f8cdd47d4661de14b56f68de6ddf50c4f76a81f7ebed6046744d1e63",
"mainChain": true
},
{
"boxId": "909176f27e0ebf3abca835f29f2bd739773ba05e4b82315874a34a1ff54046ca",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 7,
"globalIndex": 31354011,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "759692e2bb40310ced36b2c337cba7a0395ba7c51cfd2251c9ad026e0dff3b0e",
"index": 0,
"amount": 1,
"name": "Mage Champions #880",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "179b114a42f4ade6d5c4989403b8b67e40325f01ac0a7e43138620c934b7347d",
"mainChain": true
},
{
"boxId": "d2f853d989a46a6bc513e5e0c67c6b206d4a12453abfcbc359ced41aecb5f3ed",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 8,
"globalIndex": 31354012,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "8e42f722117b8a78b5707a4e395aa68d18d86327fd09d2f8dcf21e138da93726",
"index": 0,
"amount": 1,
"name": "Mage Champions #903",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "a601fe5b971e5ad2e108bceb1d718d9a3ea195096aecbe6000cd6da7325c26f8",
"mainChain": true
},
{
"boxId": "333c762d27af9ef13faecf94b76cca30f9ac3d284e6893c6030c0ddadc070a6f",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 9,
"globalIndex": 31354013,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "5e9bccda667dd05666d4a01f341d995540aa4cea6ebf3a33aff9658491b6db4f",
"index": 0,
"amount": 1,
"name": "Mage Champions #866",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "2661aa3268d3ceb5d4c985be04f14c87746feafb3dcdbd562bce445b595413dd",
"mainChain": true
},
{
"boxId": "fbf17d73ec31b53f6329b0c67d2d7aef09237f16c09f8a5db0f043a162ac021f",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 10,
"globalIndex": 31354014,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "147b4234ded25a11d186cee547cf2440856aa4a64b1c47e4fde32353dc57b9e7",
"index": 0,
"amount": 1,
"name": "Mage Champions #1008",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "094fbeac84a6a6a485d4bfcb7e57e021159c7c871fc39f54e03ff757d1c85a5d",
"mainChain": true
},
{
"boxId": "ef76ce689533c59a423a07ec8705efe031e6e10ece12f6cda221cb840f3c20d4",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 11,
"globalIndex": 31354015,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "2a03c98de16ea6ade7f5ac4ed1ab4179d154bffd6c86514ca63de56eb333ef68",
"index": 0,
"amount": 1,
"name": "Mage Champions #623",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "1e41adff7aa095f2daebf9f94375710be1b98ed0caa4c7c4efa72ba3bd263daf",
"mainChain": true
},
{
"boxId": "f34bb770f35dee8de5923c65c925a051f16c49ed3dfe36adc2506660aef21730",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 12,
"globalIndex": 31354016,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "090eda4bd30c346093ed13d609b1dd84047886405f7081ad39054163f2ccd479",
"index": 0,
"amount": 1,
"name": "Mage Champions #1210",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "356af666591531c8fd43f430698662ec2ad2ba91cd370907f2963b4a0a6e171e",
"mainChain": true
},
{
"boxId": "93ef697ce8ea9fbb077d4140466e1a91bb07fe313c259066859b5351ed8881d4",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 13,
"globalIndex": 31354017,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "959ad19b2c6c9e1f8aeeba81a6d4b2ad030f88f757e13e8ffbed8bde60db1dba",
"index": 0,
"amount": 1,
"name": "Mage Champions #507",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "0774df4554cd6467a83e5d3241c02bfb94f8e04a8cfc75ac64e8a5ac2e368c35",
"mainChain": true
},
{
"boxId": "4bc10ed666240f904f80b919fbafcf1efc7ce638acc7b01857b952d7821dfe2a",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 14,
"globalIndex": 31354018,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "103e0402040005000400040404000402040004000400040204060500040604000504040204d00f0400040404140404040004000400040004000406040005d00f05d00f05d00f0400040404140406040005d00f040405d00f0400040604060400050001000101040204000402040004000500040004020400040204040500010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed824d601db6308a7d602830002d603c1a7d604b27201730001860272027203d6058c720402d606c6a70611d607e47206d608b27207730100d609e4c6a7070ed60a95ec8f72057208948c720401720973027205d60be4c6a7040ed60cdb6903db6503fed60de4c6a70559d60e8c720d01d60f8c720d02d610b2db6501fe730300d611e4c672100404d612b2a5730401a7d613db63087212d614c17212d615860272027214d616b272137305017215d617b2a5730601a7d618db63087217d619c17217d61a860272027219d61bb27218730701721ad61ce4c6a7080ed61d93c5b2a4730800c5a7d61eb2a5730900d61fdb6308721ed620c1721ed621860272027220d622b2721f730a017221d6238c722202d624b27207730b01730cea02eb02ea02d18f720a7208cdeeb4720b730db1720bd19591720c720e9591720c720fd813d625b1a5d626b2a5730e00d6279c730fe4c672100605d6287212d6297213d62a7214d62b7215d62c7216d62d7217d62ee5c6722d0463b2a5997225731000d62fc6722e0404d630e6722fd631999973117211957230d801d631e5722f731295ec8f723173139272317314723195ed9372317315e6c6722e050c4c0eb0e5c6722e050c4c0e83004c0e7316d90132404c0e9a8c7232018c8c7232020273177318d6327218d6337219d634721ad635721bd636b2a5731901a7d637b27201731a00eced8f720a720896830401937225731b93db63087226720192c17226997203722793c27226720bed92720a720896830601721deded93c27228720b928c722c029591b17209731c9d9c720a7e723105731d999d9c720a7e723105731e7227938c722c017209eded93c2722de4c67210050e928c7235029d9c720a7e721105731f938c723501720993c27236721c937237b2db63087236732000ed957230d801d638e4722f95ec8f723873219272387322d802d639b2a5732301a7d63ab2db6308723973240186027202c17239eded928c723a029d9c720a7e7238057325938c723a01720993c27239c2722e95ed9372387326e6c6722e050c4c0ed802d639e5c6722e050c4c0e83004c0ed63ab1723993b4ad7239d9013b4c0e86028c723b019d9c7e8c723b0205720a73277328723aadb4a573299a732a723ad9013b63d801d63db2db6308723b732b0186027202c1723b95938c723d0172098602c2723b8c723d0286027202732c732d732e93cbc3722e8c723701d808d625721ed626721fd6277220d6287221d6297222d62ae4c672100711d62bb2a5732f00d62cb2db6308722b73300186027202c1722b96830c01721d938c7229017209927223a29a720ab27207733100720893b27201733200b2722673330093c27225c2a793e4c67225040e720b93e4c6722505598602720e95ed9172247334d801d62d722392722d7224720c959099720f720cb2722a7335009a720fb2722a733600720f93c672250611720693e4c67225070e720993b172269593b1720973377338733993c2722b721ceced938c722c017209928c722c02720a93720a733a733bd1938cb2db63087210733c0001733d",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
"address": "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",
"assets": [
{
"tokenId": "a011acc4d0a6f622e0f34fd78f8460d468397526efe5a0333513a3ee4abac2be",
"index": 0,
"amount": 1,
"name": "Mage Champions #513",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59e2b3ad85b462c0d9fcfbb562",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "1fe8b9edbbdf392b10382b7cc329b0651fcbb8e782c695bac38306e0f1bec87b",
"mainChain": true
},
{
"boxId": "affc62faf716ddbe6a773e9f70671f05a44188affa498244087e90f9b6be79fa",
"transactionId": "db8eadef6d61b2cedf50aaabe8100fd0a3e5043674ef74a49cb0eefbf06ead15",
"blockId": "ed6c764a51fead2423ef4dd21068a3b583d84a8a991446b43775babfac1793eb",
"value": 15000000,
"index": 15,
"globalIndex": 31354019,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "103e0402040005000400040404000402040004000400040204060500040604000504040204d00f0400040404140404040004000400040004000406040005d00f05d00f05d00f0400040404140406040005d00f040405d00f0400040604060400050001000101040204000402040004000500040004020400040204040500010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed824d601db6308a7d602830002d603c1a7d604b27201730001860272027203d6058c720402d606c6a70611d607e47206d608b27207730100d609e4c6a7070ed60a95ec8f72057208948c720401720973027205d60be4c6a7040ed60cdb6903db6503fed60de4c6a70559d60e8c720d01d60f8c720d02d610b2db6501fe730300d611e4c672100404d612b2a5730401a7d613db63087212d614c17212d615860272027214d616b272137305017215d617b2a5730601a7d618db63087217d619c17217d61a860272027219d61bb27218730701721ad61ce4c6a7080ed61d93c5b2a4730800c5a7d61eb2a5730900d61fdb6308721ed620c1721ed621860272027220d622b2721f730a017221d6238c722202d624b27207730b01730cea02eb02ea02d18f720a7208cdeeb4720b730db1720bd19591720c720e9591720c720fd813d625b1a5d626b2a5730e00d6279c730fe4c672100605d6287212d6297213d62a7214d62b7215d62c7216d62d7217d62ee5c6722d0463b2a5997225731000d62fc6722e0404d630e6722fd631999973117211957230d801d631e5722f731295ec8f723173139272317314723195ed9372317315e6c6722e050c4c0eb0e5c6722e050c4c0e83004c0e7316d90132404c0e9a8c7232018c8c7232020273177318d6327218d6337219d634721ad635721bd636b2a5731901a7d637b27201731a00eced8f720a720896830401937225731b93db63087226720192c17226997203722793c27226720bed92720a720896830601721deded93c27228720b928c722c029591b17209731c9d9c720a7e723105731d999d9c720a7e723105731e7227938c722c017209eded93c2722de4c67210050e928c7235029d9c720a7e721105731f938c723501720993c27236721c937237b2db63087236732000ed957230d801d638e4722f95ec8f723873219272387322d802d639b2a5732301a7d63ab2db6308723973240186027202c17239eded928c723a029d9c720a7e7238057325938c723a01720993c27239c2722e95ed9372387326e6c6722e050c4c0ed802d639e5c6722e050c4c0e83004c0ed63ab1723993b4ad7239d9013b4c0e86028c723b019d9c7e8c723b0205720a73277328723aadb4a573299a732a723ad9013b63d801d63db2db6308723b732b0186027202c1723b95938c723d0172098602c2723b8c723d0286027202732c732d732e93cbc3722e8c723701d808d625721ed626721fd6277220d6287221d6297222d62ae4c672100711d62bb2a5732f00d62cb2db6308722b73300186027202c1722b96830c01721d938c7229017209927223a29a720ab27207733100720893b27201733200b2722673330093c27225c2a793e4c67225040e720b93e4c6722505598602720e95ed9172247334d801d62d722392722d7224720c959099720f720cb2722a7335009a720fb2722a733600720f93c672250611720693e4c67225070e720993b172269593b1720973377338733993c2722b721ceced938c722c017209928c722c02720a93720a733a733bd1938cb2db63087210733c0001733d",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val coll11 = SELF.R4[Coll[Byte]].get\n val l12 = CONTEXT.preHeader.timestamp\n val tuple13 = SELF.R5[(Long, Long)].get\n val l14 = tuple13._1\n val l15 = tuple13._2\n val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n val i17 = box16.R4[Int].get\n val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll19 = box18.tokens\n val l20 = box18.value\n val tuple21 = (coll2, l20)\n val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll24 = box23.tokens\n val l25 = box23.value\n val tuple26 = (coll2, l25)\n val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n val coll28 = SELF.R8[Coll[Byte]].get\n val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n val box30 = OUTPUTS(placeholder[Int](9))\n val coll31 = box30.tokens\n val l32 = box30.value\n val tuple33 = (coll2, l32)\n val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n val l35 = tuple34._2\n val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n val i37 = OUTPUTS.size\n val box38 = OUTPUTS(placeholder[Int](14))\n val l39 = placeholder[Long](15) * box16.R6[Long].get\n val box40 = box18\n val coll41 = coll19\n val l42 = l20\n val tuple43 = tuple21\n val tuple44 = tuple22\n val box45 = box23\n val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n val opt47 = box46.R4[Int]\n val bool48 = opt47.isDefined\n val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n val i49 = opt47.getOrElse(placeholder[Int](18))\n if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n )} else { placeholder[Int](24) }\n val coll50 = coll24\n val l51 = l25\n val tuple52 = tuple26\n val tuple53 = tuple27\n val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n val tuple55 = coll1(placeholder[Int](26))\n ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n val i56 = opt47.get\n if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i58 = coll57.size\n coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n })\n )} else { placeholder[Boolean](45) } }\n )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n )} else {(\n val box37 = box30\n val coll38 = coll31\n val l39 = l32\n val tuple40 = tuple33\n val tuple41 = tuple34\n val coll42 = box16.R7[Coll[Long]].get\n val box43 = OUTPUTS(placeholder[Int](47))\n val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n val l45 = l35\n l45 >= l36\n ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
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"assets": [
{
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"index": 0,
"amount": 1,
"name": "Mage Champions #940",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
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"sigmaType": "(SLong, SLong)",
"renderedValue": "[1690612116721,1690870716000]"
},
"R6": {
"serializedValue": "110280acc7f03780a8d6b907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[7500000000,1000000000]"
},
"R8": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa"
}
},
"spentTransactionId": "5afa71bf549f962f5db7b7acf846d871c9fbf01a10812120d6cb2e65fc9b6268",
"mainChain": true
},
{
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"index": 16,
"globalIndex": 31354020,
"creationHeight": 1057315,
"settlementHeight": 1057317,
"ergoTree": "0008cd034970f9cc6ef50c406985ba1457fc9e52b37f4cec4bc5ea31cde18d510e9298aa",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(4970f9,ce1e2c,...)))}",
"address": "9h29eioRvrL86Sabpecor9ag6rfXEGQt7U3K9q3Di1fdA4jVEsp",
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{
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{
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{
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{
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"additionalRegisters": {},
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{
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(240e71,dfb102,...)))}",
"address": "9gjghouPwq9TCKyFAAvHPsoE1n9moZWec9oKeRzAjnV9p4hAzvo",
"assets": [],
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{
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"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
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"mainChain": true
}
],
"size": 23739,
"isUnconfirmed": false
}